Notice of Violation of IEEE Publication PrinciplesBusiness Blog Mining Based on Hierarchical SVM

Notice of Violation of IEEE Publication Principles

"Business Blog Mining Based on Hierarchical SVM","
by Huiling Wang,
in the Proceedings of the 2008 International Symposium on Knowledge Acquisition and Modeling, December 2008, pp 837-841

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.

This paper contains substantial portions of the original text from the papers cited below. The original text was copied without attribution and without permission.

"Machine Learning Techniques for Business Blog Search and Mining,"
by Yun Chen, Flora S. Tsai and Kap Luk Chan,
in Expert Systems with Applications, 35 (2008) October 2004, pp 581-590, ElsevierBlog has rapidly gained in popularity in the past decade. In particular, the growth of business blogs, written by professionals and providing commentary on businesses and companies, opens up new opportunities for developing blog knowledge mining techniques. In this paper, we propose hierarchical SVM model for blog mining. We implement the model in our database of business blogs with the aim of achieving better effect of blog mining. The hierarchical model is able to segment the business blogs into separate areas, which is useful for knowledge detection on the blogosphere. Various term-weighting schemes and factor values were also studied in detail, which reveal interesting patterns in our database of business blogs. Our multi-functional business blog mining system is found to be different from existing blog mining system, as it aims to provide better effects of business blog mining.